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- 🤖 Microsoft’s $80 Billion AI Infrastructure Investment
🤖 Microsoft’s $80 Billion AI Infrastructure Investment
PLUS: Google DeepMind Tackles AI’s “Peak Data” Problem, AI-Related Job Titles Have Tripled Since 2022

Welcome back AI enthusiasts!
In today’s Daily Report:
🚜Microsoft’s $80 Billion AI Infrastructure Investment
⚙️Google DeepMind Tackles AI’s “Peak Data” Problem
📈AI-Related Job Titles Have Tripled Since 2022
🛠Trending Tools
💰Funding Frontlines
💼Who’s Hiring?
Read Time: 3 minutes
🗞RECENT NEWS
MICROSOFT
🚜Microsoft’s $80 Billion AI Infrastructure Investment
Microsoft revealed plans to invest $80 billion into building data centers that house AI Clusters to power advanced AI applications.
Key Details:
Over half of the $80 billion will be focused on building data centers in America to gain an edge over Chinese competitors.
Vice Chair and President of Microsoft Brad Smith outlined a three-part vision for America’s AI success:
Investing in AI Infrastructure
Exporting American AI to Allies and Friends
Skilling Programs to Promote Widespread AI Adoption
An AI Cluster combines the power, storage, and memory of GPUs to train, develop, and deploy advanced AI applications.
Why It’s Important:
These data centers reduce compute constraints for the company’s developers, allowing them to power advanced AI applications.
This investment enables Microsoft to build bigger, better, and faster AI models with excellent scalability, flexibility, and performance.
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GOOGLE DEEPMIND
⚙️Google DeepMind Tackles AI’s “Peak Data” Problem

Image Source: Google DeepMind/“Scaling LLM Test-Time Compute Optimally Can Be More Efficient Than Scaling Model Parameters”/Screenshot
Google DeepMind has found a new approach to overcome data limitations when training AI models.
Key Details:
OpenAI’s former Chief Scientist Ilya Sutskever recently explained: “We’ve achieved peak data, and there’ll be no more.”
AI firms have already used all the useful data available on the internet to train AI models. “We’ve hit a data wall,” added Sutskever.
To solve this issue, Google DeepMind developed Test-Time Compute, which allocates more computing power during AI Inference: everything that happens after you enter your prompt.
This process allows AI models to “think harder” on complex problems by exploring multiple ways to answer your prompt. It achieves this by breaking down your prompt into smaller tasks.
Now, Google DeepMind is using these smaller tasks as new training data in a process known as the Iterative Self-Improvement Loop.
Why It’s Important:
All the useful data on the internet has already been used to train AI models. Also, all high-quality data could be exhausted by 2026.
Test-Time Compute and the Iterative Self-Improvement Loop are Google DeepMind’s innovative approaches to overcome data limitations when training AI models.
AI TRENDS
📈AI-Related Job Titles Have Tripled Since 2022

Image Source: Canva’s AI Image Generators/Magic Media
ZoomInfo, a platform to find, acquire, and grow customers, published a report showcasing how AI-related job titles across industries, sectors, and skill levels have tripled since 2022.
The Key Takeaways Include:
AI-related job titles in leadership roles are three times (i.e., 3x) more prevalent than before:
AI-based Managers are up 174% from 1,894 to 5,208.
AI-based Directors are up 197% from 1,264 to 3,756.
AI-based Executives are up 428% from 81 to 428.
The term “Engineer” is associated with 48% of AI-specific job titles, followed by similar technical disciplines such as “Researcher,” “Developer,” or “Scientist.”
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📊UniDeck creates personalized dashboards in minutes.
📋MirWork turns any job listing on LinkedIn into a mock interview.
👷Visionari collects, analyzes, and acts on user feedback for you.
🎙️GitPodcast transforms a GitHub repository into an engaging podcast.
🔮Browse our always Up-To-Date AI Tools Database.
💰FUNDING FRONTLINES
Rembrand closes a $23M Funding Round to offer AI-powered virtual product placements.
Cimulate AI secures a $28M Series A to help brands connect with and convert potential buyers.
Accel raises a $650M Early-Stage Fund for startups in India and Southeast Asia to acquire AI talent.
💼WHO’S HIRING?
Visa (Austin, TX): Software Engineer Intern, Summer 2025
Fastly (San Francisco, CA): Software Engineer Intern, Summer 2025
Groq (Palo Alto, CA): AI Application Engineering Intern, Summer 2025
Meta (Burlingame, CA): Embedded Software Engineer Intern, Summer 2025
NVIDIA (Santa Clara, CA): Technical Marketing Intern, 3D Pipeline and Tech Art, Summer 2025
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